Metadata-Version: 2.1
Name: armagarch
Version: 1.0
Summary: Library for flexible mean and volatility modelling
Home-page: https://github.com/iankhr/armagarch
Author: Ian Khrashchevskyi
Author-email: iankhr@yahoo.com
License: UNKNOWN
Description: # armagarch package
        The package provides a flexible framework for modelling time-series data. The main focus of the package is implementation of the ARMA-GARCH type models.
        
        **Full documentation and installation instruction coming soon.**
          
        
        ## Example: Modelling conditional volatility of the US excess market returns
        
        The code requires: NumPy, Pandas, SciPy, Shutil, Matplotlib, Pandas_datareader and Statsmodels
        
        
        ```
        import armagarch as ag
        import pandas_datareader as web
        import matplotlib.pyplot as plt
        import numpy as np
        
        # load data from KennethFrench library
        ff = web.DataReader('F-F_Research_Data_Factors_daily', 'famafrench')
        ff = ff[0]
        
        # define mean, vol and distribution
        meanMdl = ag.ARMA(order = {'AR':1,'MA':0})
        volMdl = ag.garch(order = {'p':1,'o':1,'q':1})
        distMdl = ag.normalDist()
        
        # create a model
        model = ag.empModel(ff['Mkt-RF'].to_frame(), meanMdl, volMdl, distMdl)
        # fit model
        model.fit()
        
        # get the conditional mean
        Ey = model.Ey
        
        # get conditional variance
        ht = model.ht
        cvol = np.sqrt(ht)
        
        # get standardized residuals
        stres = model.stres
        
        ````
        
        
        ## Authors
        
        * **Ian Khrashchevskyi** - [iankhr](https://github.com/iankhr)
        
        ## License
        
        This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
        
        ## Acknowledgments
        
        * Special thanks to Kevin Sheppard for his [Python for Econometrics](https://www.kevinsheppard.com/Python_for_Econometrics), which was an inspiration to write current code
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
